• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1018-1020
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• 2013

Conventionally, PCB fabrication processes detects simply electrical characteristics of TCP and COF by automatic manufacturing system and additionally, by introducing human visual detection, those are very ineffective in view of low cost implementation. So, this paper presents an efficient detection algorithm for short and protrusion-type defects based on reference images by using local binary pattern analysis. The proposed methods include several preprocessing techniques such as histogram equalizing, the compensation of spatial position and maximum distortion coordination Through several experiments, it is shown that the proposed method can improve the defect detection performance compared to the conventional schemes.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Transactions of Materials Processing
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• v.25 no.6
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• pp.353-358
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• 2016

Direct energy deposition (DED) is an additive manufacturing technique that involves the melting of metal powder with a high-powered laser beam and is used to build a variety of components. In recent year, it can be widely used in order to produce hard, wear resistant and/or corrosion resistant surface layers of metallic mechanical parts, such as dies and molds. For the purpose of the hardfacing to achieve high wear resistance and hardness, application of high speed steel (HSS) can be expected to improve the tool life. During the DED process using the high-carbon steel, however, defects (delamination or cracking) can be induced by rapid solidification of the molten powder. Thus, substrate preheating is generally adopted to reduce the deposition defect. While the substrate preheating ensures defect-free deposition, it is important to select the optimal preheating temperature since it also affects the microstructure evolution and mechanical properties. In this study, AISI M4 powder was deposited on the AISI 1045 substrate preheated at different temperatures (room temperature to $500^{\circ}C$). In addition, the micro-hardness distribution, cooling rates, and microstructures of the deposited layers were investigated in order to observe the influence of the substrate preheating on the mechanical and metallurgical properties.

• Progress in Superconductivity and Cryogenics
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• v.21 no.3
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• pp.43-46
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• 2019

A rare-earth barium copper oxide (REBCO) superconducting magnet was designed using no-insulation (NI) and multi-width (MW) winding techniques. The proposed magnet is comprised of 58 REBCO-wound single pancake coils with a bore size of 240 mm. When the magnet is operated at 20 K, the center magnetic flux density is designed to reach 3 T with an operational current of 169.55 A, 70 % of its critical current. The critical current was evaluated using experimental data of a short REBCO conductor sample. The designed magnet was then simulated using FEM software with uniform current density model. Magnetic field and mechanical properties of the magnet are evaluated using the simulated data. This magnet was designed as one of the base designs for the project "Tesla-Level Magnets with Large Bore Sizes for Industrial Applications" which was initiated in 2019, and will be wound using REBCO wires with the defect-irrelevant-winding (DIW) technique incorporated to reduce the overall manufacturing cost.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.32-32
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• 2009

Electric Resistance Welding (ERW) process is the most efficient process to manufacture the linepipe. To develop the high performance ERW linepipe using the high strength and the high alloy steels, the modulation of input power waveform such as sinusoidal waveform is introduced because the conventional ERW technology is not sufficient enough to produce the high quality linepipe due to its strength and high alloy contents (high Ceq). In this article, the material used for the experiment was API X60 with 8.2mm thickness, and ERW simulator at POSCO was used to develop a waveform control system for the power modulation. The frequency of power modulation was varied from 50Hz to 150Hz with the fixed amplitude of ${\pm}2%$ power. The non-modulated power input and the modulated power input cases are conducted to demonstrate the variation of the narrow gap length and the arcing frequency due to power modulation. From results of the non-modulated power input case, the excessive power causes the longer narrow gap length and the low arcing frequency due to the large heat input and the strong electro magnetic force that increase the weld defect. On the contrary, the small narrow gap length and the high arcing frequency reduce the weld defect. After modulating the power input with 50Hz and 100Hz at the fixed power, the arcing frequency increases, but the narrow gap length does not change much. The high arcing frequency prevents the formation of weld defect because the sweeping frequently cleans the oxides on the narrow gap edges. As a result, the manufacturing window can be expanded by the power modulation that provides the stable ERW process for the quality improvement of the linepipe made from the high strength/high alloy steels.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.120-126
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• 2009

There are many different types of surface defects on semiconductor Integrated Chips (IC's) caused by various factors during manufacturing process, such as cracks, foreign materials, chip-outs, chips, and voids. These defects must be detected and classified by an inspection system for productivity improvement and effective process control. Among defects, in particular, foreign materials and chips are the most difficult ones to classify accurately. A vision system composed of a carefully designed optical system and a processing algorithm is proposed to detect and classify the defects on QFN(Quad Flat No-leads) packages. The processing algorithm uses features derived from the defect's position and brightness value in the Maximum Likelihood classifier and the optical system is designed to effectively extract the features used in the classifier. In experiments we confirm that this method gives more effective result in classifying foreign materials and chips.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.112-120
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• 2000

In this paper, we implement a real-time textile dimension inspection system. It can detect various types of real defects which determine the quality of fabric product, defect positions of textile, classify the distortion angel of moving textile and the density. In the implemented system, we measure the density of textile using zone-crossing method with optical lens to solve the noise and real-time problems. And we compensate distortion angel of textile with the classification of distortion types using gaussian gradient and mean gradient features. And also, it detecs real defects of textile and its positions using gray level co-occurrence matrix features. The implemented texile demension inspection systemcan inspect textile dimensions such as density, distortion angle, defect of textile and defect position at real-time. In the implemented proposed texitile dimension inspection system, It is possible to calculate density and detect default of textile at real-time dimension inspection system, it is possible to calculate density and detect default of textile at textile states throughout at all the significant working process such as dyeing, manufacturing, and other texitle processing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.102-114
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• 2021

NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.107-116
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• 2024

Copper Filter Dryer (CFD) are responsible for removing impurities from the circulation of refrigerant in refrigeration and cooling systems to maintain clean refrigerant, and defects in CFD can lead to product defects such as leakage and reduced lifespan in refrigeration and cooling systems, making quality assurance essential. In the quality inspection stage, human inspection and defect judgment methods are traditionally used, but these methods are subjective and inaccurate. In this paper, YOLOv7 object detection algorithm was used to detect defects occurring during the CFD Shaft pipe and welding process to replace the existing quality inspection, and the detection performance of F1-Score 0.954 and 0.895 was confirmed. In addition, the cause of defects occurring during the welding process was analyzed by analyzing the sensor data corresponding to the Timestamp of the defect image. This paper proposes a method for manufacturing quality assurance and improvement by detecting defects that occur during CFD process and analyzing their causes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1274-1279
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• 2011

The purpose of this paper is to present the manufacturing defect and damage pattern of a 3 phase 22.9/3.3kV oil immersed transformer, as well as to present an objective basis for the prevention of a similar accident and to secure data for the settlement of PL related disputes. It was found that in order to prevent the occurrence of accidents to transformers, insulating oil analysis, thermal image measurement, and corona discharge diagnosis, etc., were performed by establishing relevant regulation. The result of analysis performed on the external appearance of a transformer to which an accident occurred, the internal insulation resistance and protection system, etc., showed that most of the analysis items were judged to be acceptable. However, it was found that the insulation characteristics between the primary winding and the enclosure, those between the ground and the secondary winding, and those between the primary and secondary windings were inappropriate due to an insulating oil leak caused by damage to the pressure relief valve. From the analysis of the acidity values measured over the past 5 years, it is thought that an increase in carbon dioxide (CO2) caused an increase in the temperature inside the transformer and the increase in the ethylene gas increased the possibility of ignition. Even though 17 years have passed since the transformer was installed, it was found that the system's design, manufacture, maintenance and management have been performed well and the insulating paper was in good condition, and that there was no trace of public access or vandalism. However, in the case of transformers to which accidents have occurred, a melted area between the upper and the intermediate bobbins of the W-phase secondary winding as well as between its intermediate and lower bobbins. It can be seen that a V-pattern was formed at the carbonized area of the transformer and that the depth of the carbonization is deeper at the upper side than the lower side. In addition, it was found that physical bending and deformation occurred inside the secondary winding due to non-uniform pressure while performing transformer winding work. Therefore, since it is obvious that the accident occurred due to a manufacturing defect (winding work defect), it is thought that the manufacturer of the transformer is responsible for the accident and that it is lawful for the manufacture to investigate and prove the concrete cause of the accident according to the Product Liability Law (PLL).